Then all outcomes will be tested in comparison of the intervention and control group with multifactorial regression models on an intention-to-treat basis.
In conclusion, by studying the association between a limited panel of genetic variants and nephropathy risk, we developed a robust multifactorial logistic regression model to predict nephropathy in our study populations.
These data were analysed with a multifactorial linear regression model.
20– 23 Therefore, the purpose of the current study was to present a multifactorial logistical regression model incorporating the involved cervical lymph node level at the time of presentation and epidemiologic data to calculate the probability of an H&N tumor site of origin for patients with SCC confined to the cervical lymph nodes.
More recently, Easton and colleagues have provided multifactorial logistic regression models to classify UVs in the BRCA genes [ 14].
To estimate the effect of treatment modality on the peak values of inflammatory parameters with adjustment for the potential confounding factors, multifactorial linear regression models were used.
The ASA scores of the patients were, however, included in multifactorial linear regression models and they did not affect the results.
In conclusion, the increased risk for developing a multifactorial disease based upon disease-susceptibility variants with moderate effects was estimated using a logistic regression model assuming multiplicative gene gene interactions.
Multiple regression models, and the logistic regression model in particular, have a long history in the analysis of epidemiological studies of multifactorial disease.
Statistical models have revealed strong positive association between circulating leptin and SUA, and in multifactorial regression analyses serum leptin could explain 34-42% of the variance in SUA in both men and women in a hypertensive cohort of Turkish patients[101].
